apify-audience-analysis

name	apify-audience-analysis
description	Understand audience demographics, preferences, behavior patterns, and engagement quality across Facebook, Instagram, YouTube, and TikTok.
risk	unknown
source	community

Audience Analysis

Analyze and understand your audience using Apify Actors to extract follower demographics, engagement patterns, and behavior data from multiple platforms.

When to Use

• You need audience demographics, engagement patterns, or follower behavior from social platforms.
• The task is to choose and run Apify Actors for audience analysis across Facebook, Instagram, YouTube, or TikTok.
• You need structured extraction plus a summarized interpretation of audience findings.

Prerequisites

(No need to check it upfront)

• .env file with APIFY_TOKEN
• Node.js 20.6+ (for native --env-file support)
• mcpc CLI tool: npm install -g @apify/mcpc

Workflow

Copy this checklist and track progress:

Task Progress:
- [ ] Step 1: Identify audience analysis type (select Actor)
- [ ] Step 2: Fetch Actor schema via mcpc
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the analysis script
- [ ] Step 5: Summarize findings

Step 1: Identify Audience Analysis Type

Select the appropriate Actor based on analysis needs:

User Need	Actor ID	Best For
Facebook follower demographics	apify/facebook-followers-following-scraper	FB followers/following lists
Facebook engagement behavior	apify/facebook-likes-scraper	FB post likes analysis
Facebook video audience	apify/facebook-reels-scraper	FB Reels viewers
Facebook comment analysis	apify/facebook-comments-scraper	FB post/video comments
Facebook content engagement	apify/facebook-posts-scraper	FB post engagement metrics
Instagram audience sizing	apify/instagram-profile-scraper	IG profile demographics
Instagram location-based	apify/instagram-search-scraper	IG geo-tagged audience
Instagram tagged network	apify/instagram-tagged-scraper	IG tag network analysis
Instagram comprehensive	apify/instagram-scraper	Full IG audience data
Instagram API-based	apify/instagram-api-scraper	IG API access
Instagram follower counts	apify/instagram-followers-count-scraper	IG follower tracking
Instagram comment export	apify/export-instagram-comments-posts	IG comment bulk export
Instagram comment analysis	apify/instagram-comment-scraper	IG comment sentiment
YouTube viewer feedback	streamers/youtube-comments-scraper	YT comment analysis
YouTube channel audience	streamers/youtube-channel-scraper	YT channel subscribers
TikTok follower demographics	clockworks/tiktok-followers-scraper	TT follower lists
TikTok profile analysis	clockworks/tiktok-profile-scraper	TT profile demographics
TikTok comment analysis	clockworks/tiktok-comments-scraper	TT comment engagement

Step 2: Fetch Actor Schema

Fetch the Actor's input schema and details dynamically using mcpc:

export $(grep APIFY_TOKEN .env | xargs) && mcpc --json mcp.apify.com --header "Authorization: Bearer $APIFY_TOKEN" tools-call fetch-actor-details actor:="ACTOR_ID" | jq -r ".content"

Replace ACTOR_ID with the selected Actor (e.g., apify/facebook-followers-following-scraper).

This returns:

• Actor description and README
• Required and optional input parameters
• Output fields (if available)

Step 3: Ask User Preferences

Before running, ask:

1. Output format:
   • Quick answer - Display top few results in chat (no file saved)
   • CSV - Full export with all fields
   • JSON - Full export in JSON format
2. Number of results: Based on character of use case

Step 4: Run the Script

Quick answer (display in chat, no file):

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT'

CSV:

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.csv \
  --format csv

JSON:

node --env-file=.env ${CLAUDE_PLUGIN_ROOT}/reference/scripts/run_actor.js \
  --actor "ACTOR_ID" \
  --input 'JSON_INPUT' \
  --output YYYY-MM-DD_OUTPUT_FILE.json \
  --format json

Step 5: Summarize Findings

After completion, report:

• Number of audience members/profiles analyzed
• File location and name
• Key demographic insights
• Suggested next steps (deeper analysis, segmentation)

Error Handling

APIFY_TOKEN not found - Ask user to create .env with APIFY_TOKEN=your_token mcpc not found - Ask user to install npm install -g @apify/mcpc Actor not found - Check Actor ID spelling Run FAILED - Ask user to check Apify console link in error output Timeout - Reduce input size or increase --timeout